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Add Yolo-V2-Tiny
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Darknet model from: https://pjreddie.com/darknet/yolov2/
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Converted to Caffe with:
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- evgencnn/scripts/evconvert/darknet2ev/create_yolo_prototxt.py
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- evconvert/darknet2ev/create_yolo_caffemodel.py
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version https://git-lfs.github.com/spec/v1
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oid sha256:2fdc4c5c93f7b0bee275fbc881e685cacbe055cf327d774a0f6df4ce13b78642
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size 63474120
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[net]
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# Testing
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batch=1
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subdivisions=1
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# Training
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# batch=64
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# subdivisions=2
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width=416
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height=416
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channels=3
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momentum=0.9
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decay=0.0005
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angle=0
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saturation = 1.5
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exposure = 1.5
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hue=.1
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learning_rate=0.001
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max_batches = 40200
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policy=steps
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steps=-1,100,20000,30000
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scales=.1,10,.1,.1
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[convolutional]
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batch_normalize=1
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filters=16
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size=3
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stride=1
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pad=1
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activation=leaky
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[maxpool]
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size=2
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stride=2
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[convolutional]
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batch_normalize=1
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filters=32
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size=3
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stride=1
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pad=1
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activation=leaky
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[maxpool]
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size=2
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stride=2
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[convolutional]
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batch_normalize=1
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filters=64
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size=3
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stride=1
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pad=1
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activation=leaky
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[maxpool]
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size=2
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stride=2
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[convolutional]
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batch_normalize=1
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filters=128
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size=3
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stride=1
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pad=1
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activation=leaky
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[maxpool]
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size=2
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stride=2
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[convolutional]
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batch_normalize=1
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filters=256
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size=3
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stride=1
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pad=1
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activation=leaky
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[maxpool]
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size=2
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stride=2
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[convolutional]
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batch_normalize=1
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filters=512
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size=3
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stride=1
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pad=1
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activation=leaky
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[maxpool]
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size=2
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stride=1
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[convolutional]
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batch_normalize=1
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filters=1024
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size=3
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stride=1
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pad=1
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activation=leaky
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###########
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[convolutional]
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batch_normalize=1
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size=3
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stride=1
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pad=1
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filters=1024
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activation=leaky
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[convolutional]
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size=1
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stride=1
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pad=1
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filters=125
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activation=linear
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#[region]
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#anchors = 1.08,1.19, 3.42,4.41, 6.63,11.38, 9.42,5.11, 16.62,10.52
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#bias_match=1
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#classes=20
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#coords=4
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#num=5
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#softmax=1
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#jitter=.2
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#rescore=1
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#
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#object_scale=5
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#noobject_scale=1
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#class_scale=1
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#coord_scale=1
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#
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#absolute=1
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#thresh = .6
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#random=1

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